Deep Inference of Personality Traits by Integrating Image and Word Use in Social Networks
Social media, as a major platform for communication and information exchange, is a rich repository of the opinions and sentiments of 2.3 billion users about a vast spectrum of topics. To sense the whys of certain social user's demands and cultural-driven interests, however, the knowledge embedded in the 1.8 billion pictures which are uploaded daily in public profiles has just started to be exploited since this process has been typically been text-based. Following this trend on visual-based social analysis, we present a novel methodology based on Deep Learning to build a combined image-and-text based personality trait model, trained with images posted together with words found highly correlated to specific personality traits. So the key contribution here is to explore whether OCEAN personality trait modeling can be addressed based on images, here called \emph{Mind{P}ics}, appearing with certain tags with psychological insights. We found that there is a correlation between those posted images and their accompanying texts, which can be successfully modeled using deep neural networks for personality estimation. The experimental results are consistent with previous cyber-psychology results based on texts or images. In addition, classification results on some traits show that some patterns emerge in the set of images corresponding to a specific text, in essence to those representing an abstract concept. These results open new avenues of research for further refining the proposed personality model under the supervision of psychology experts.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
PTEI: Integrating Personality Traits to Enhance Emotional Intelligence in Large Language Models
Despite advances in Emotional Intelligence (EI), Large Language Models (LLMs) still significantly underperform humans in complex emotional reasoning. This gap originates partly from the limited incorporation of individua…
Emotional IntelligenceContrastive LearningA Recurrent and Compositional Model for Personality Trait Recognition from Short Texts
Many methods have been used to recognise author personality traits from text, typically combining linguistic feature engineering with shallow learning models, e.g. linear regression or Support Vector Machines. This work …
Feature EngineeringPart-Of-Speech TaggingPersonality Trait Recognitionregression+2A Language-independent and Compositional Model for Personality Trait Recognition from Short Texts
Many methods have been used to recognize author personality traits from text, typically combining linguistic feature engineering with shallow learning models, e.g. linear regression or Support Vector Machines. This work …
Author ProfilingFeature EngineeringPersonality Trait Recognitionregression+1Orca: Enhancing Role-Playing Abilities of Large Language Models by Integrating Personality Traits
Large language models has catalyzed the development of personalized dialogue systems, numerous role-playing conversational agents have emerged. While previous research predominantly focused on enhancing the model's capab…
Personality Estimation from Japanese Text
We created a model to estimate personality trait from authors{'} text written in Japanese and measured its performance by conducting surveys and analyzing the Twitter data of 1,630 users. We used the Big Five personality…